User:JC33123/sandbox

= Data Science at the University of Illinois Urbana-Champaign =

The Data Science program at the University of Illinois at Urbana-Champaign (UIUC) offers educational opportunities that address the growing demand for professionals skilled in data science and big data handling. The program encompasses a series of undergraduate degrees, known as X + Data Science (X + DS), which integrate data science principles with various other disciplines. These programs aim to prepare students for the challenges posed by the digital transformation of society by fostering interdisciplinary collaboration across fields and enhancing accessibility to data science education. According to the U.S. News & World Report & World Report 2024 Best Undergraduate Data Science Programs rankings, the University of Illinois Urbana-Champaign is ranked #12 in the United States.

History
The School of Information Sciences (iSchool) at UIUC has played a significant role in shaping the university's history, particularly in the context of data science. The iSchool's origins date back over a century to the establishment of a library science program led by Katharine Sharp. The program evolved through several name changes, reflecting its evolving mission: it was founded as the library science program at the Armour Institute of Technology in 1893, relocated to Urbana and became the Illinois State Library School in 1897, was rebranded as the University of Illinois Library School in 1926, the Graduate School of Library Science in 1959, the Graduate School of Library and Information Science in 1981, and eventually became the School of Information Sciences in 2016.

Advancements and Contributions in Data Science at UIUC
UIUC has recently started several initiatives to advance data science research and curriculum on campus. Here are some examples that showcases the university's involvement in this field:

Interdisciplinary Degree Programs: The university has launched a series of undergraduate degrees as part of the X + Data Science (X + DS) initiative. These programs provide an interdisciplinary approach, integrating data science with various fields to equip students with the skills needed for the demands of the digital era.

Research in Big Data Applications: UIUC faculty members actively engage in research areas driven by the applications of big data. These research endeavors encompass statistical inference, computational statistics, parallel computing, functional image analysis, climate modeling, and network analysis. This research addresses the complexities posed by the ever-growing volumes of data generated by modern technologies.

New Master's Track in CEE: The Department of Civil and Environmental Engineering at UIUC has introduced a non-thesis Master’s track that combines core CEE disciplines with data science. The curriculum aims to provide “graduate-level expertise in both data science and a technical domain in CEE”, in line with the university's efforts to incorporate data science education into its engineering programs.

Faculty Expertise: Professors at UIUC are actively involved in cutting-edge data science research. Their work spans various departments and disciplines, highlighting the university's comprehensive approach to data science education and research.

X+DS Programs
The X + Data Science (X+DS) programs at UIUC offer interdisciplinary degree paths that integrate data science with various academic disciplines. These programs aim to offer students comprehensive education in data science while allowing them to develop expertise in specific fields. Some examples of these programs are:


 * Accountancy + Data Science: This program is designed for students interested in both accounting and data science. It focuses on equipping students with skills business analysis and communication. The curriculum combines in-depth knowledge of data science with industry and functional expertise in accounting. Core courses cover various aspects of operations management, marketing, corporate finance, linear algebra, data science discovery and exploration, as well as ethics and policy for data science.


 * Astronomy + Data Science: This major provides a foundation in both data science and astronomy. Graduates are prepared to work with large astronomical data sets using contemporary computational and statistical methods. Graduates gain skills transferable across sectors such as finance, government, and insurance.


 * Business + Data Science: This major offers a broad understanding of business along with a focus on one of four specializations: Information Systems, International Business, Management, or Operations Management. Students learn to manage and interpret datasets to support informed business decision-making. The program includes core business and data science courses, with topics ranging from marketing and corporate finance to linear algebra, data science discovery, and modeling in data science.


 * Finance + Data Science: This program combines finance fundamentals with a data science component. It addresses current issues in the finance field and develops leadership skills. The curriculum covers various aspects of business and data science, including accounting, marketing, corporate finance, linear algebra, data exploration, and ethical considerations in data science.


 * Information Sciences + Data Science: This program is a collaboration between the iSchool and other colleges at UIUC, including the Gies College of Business, the Computer Science Department in Grainger Engineering College, and the Statistics Department in the College of Liberal Arts and Sciences. The curriculum encompasses information sciences, statistics, computer science, and math, preparing students for careers or further studies in these fields.

Coursework
The X + DS programs at UIUC have a structured core curriculum aimed at providing a comprehensive foundation in data science. This coursework includes:


 * Mathematical Foundations: Covering calculus and linear algebra, with a focus on their application in data science.


 * Data Science Fundamentals: Courses like Data Science Discovery, Data Science Exploration, and data modeling and machine learning, which emphasize hands-on analysis of real-world datasets, covering the entire data science pipeline.


 * Computational Fundamentals: Focused on algorithms and data structures relevant to data science and analytics.


 * Social Impact in Data Science: Including courses on ethics, policy, data management, curation, and reproducibility, addressing common ethical challenges in data science.


 * Research or Discovery Experience: Focused to engage students in research or discovery experience to apply their learning in practical, real-world contexts.

Illinois Data Science Club
The Illinois Data Science Club (iDSC) is a registered student organization (RSO) at UIUC. Its mission is to facilitate a thriving data science community by bridging the divide between academic theory and the practical application of data science. The club provides a range of opportunities for students of varying skill levels to engage in learning, collaboration, and networking within the dynamic realm of data science.

Activities:


 * Workshops and Seminars: iDSC regularly hosts workshops and seminars featuring guest speakers from academia and industry. These sessions cover a wide range of data science topics, including machine learning, natural language processing, and data visualization. The club also offers introductory workshops for beginners to provide a foundation in essential data science concepts.


 * Project-based Learning: iDSC promotes active participation in semester-long data science projects, offering students the chance to apply their theoretical knowledge to practical, real-world challenges. Working collaboratively in teams, they develop solutions and present their findings. Past projects have addressed a wide range of areas like healthcare analytics, social media analysis, and environmental data exploration.


 * Networking and Community Building: iDSC facilitates networking opportunities through various means such as social events, career panels, and mentorship programs. These events connect students with data science professionals, alumni, and faculty in the field of data science, enabling them to establish valuable connections and gain insights into potential career paths. Additionally, the club organizes hackathons and competitions to encourage friendly competition and collaboration among its members.

Online Master of Computer Science in Data Science
UIUC offers an Online Master of Computer Science in Data Science (MCS-DS) program, designed for working professionals and individuals with busy schedules seeking advanced data science skills. This fully online program provides a flexible alternative to traditional on-campus programs, allowing students to pursue their education while managing existing commitments.


 * Asynchronous Delivery: The program employs an asynchronous format, allowing students to access course materials and complete assignments independently, without the need to adhere to a fixed schedule or attend real-time lectures. Through this approach, the program aims to provides flexibility and convenience for individuals balancing work, family, or other responsibilities.


 * Rigorous Curriculum: Despite the asynchronous format, the MCS-DS maintains a rigorous curriculum. It encompasses essential computer science principles in conjunction with core data science concepts such as machine learning, data mining, data visualization, and cloud computing. The program aims to ensure that graduates possess both the theoretical knowledge and practical skills suitable for a wide range of data-driven careers.


 * Renowned Faculty: The program's faculty members are experienced researchers and instructors within the field of data science and related fields. Their expertise offers students access to a diverse range of knowledge and perspectives.

Notable Faculty
At UIUC, the data science program is supported by several esteemed faculty members who have made notable contributions to various facets of data science. Here are some of the distinguished faculty members:


 * Rachel Adler: An Associate Professor with a PhD in Computer Science, focusing on human-computer interaction, participatory design, accessible design, mobile health technologies, and computing education.


 * Catherine Blake: A Professor and Associate Dean for Academic Affairs with a PhD in Information and Computer Science specializing in biomedical informatics, evidence-based discovery, natural language processing, learning health systems, and data analytics.


 * Nigel Bosch: An Assistant Professor with a PhD in Computer Science focusing on user modeling, learning analytics, and fairness and transparency in machine learning.


 * Wade Fagen-Ulmschneider: Serving as a Teaching Associate Professor of Computer Science at UIUC, Wade Fagen-Ulmschneider has significantly impacted data science education and visualization. He has been recognized as one of the National Academy of Engineering’s Frontiers of Engineering Education scholars. He has also been awarded for innovative teaching and consistently ranked as an excellent instructor. His work in data visualizations has been widely used and featured, including by governors and major websites, and has reached millions of readers.


 * JooYoung Seo: An assistant professor in the School of Information Sciences at UIUC who is known for his expertise in data science and his focus on accessible computing. He holds the distinction of being the first blind instructor to be certified in "tidyverse". His research focuses on accessible computing, universal design, inclusive data science, and equitable healthcare technologies. JooYoung is actively involved in developing a data visualization tool aimed at making statistical data accessible to students and researchers who are visually impaired or blind.